def test_l2_matrix_rowwise():
inpt = T.matrix()
norm = l2(inpt, axis=1)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
res = f(test_matrix)
correct = np.allclose(res, np.sqrt(np.array([1.00745300e+04, 6.])))
assert correct, 'l2 norm rowwise not working'
def test_l2_matrix_colwise():
inpt = T.matrix()
norm = l2(inpt, axis=0)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
res = f(test_matrix)
correct = np.allclose(res,
[5., 1.12400000e+01, 2.42500000e+01, 1.00400400e+04])
assert correct, 'l2 norm colwise not working'
def test_l2_matrix_colwise():
inpt = T.matrix()
norm = l2(inpt, axis=0)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
res = f(test_matrix)
correct = np.allclose(
res,
np.sqrt(np.array([5., 1.12400000e+01, 2.42500000e+01, 1.00400400e+04])))
assert correct, 'l2 norm colwise not working'
def test_l2_matrix():
inpt = T.matrix()
norm = l2(inpt)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
assert np.allclose(f(test_matrix), np.sqrt(10080.53)), 'l2 norm for matrix not working'
def test_l2_vector():
inpt = T.vector()
norm = l2(inpt)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
assert np.allclose(f(test_arr), np.sqrt(6)), 'l2 norm for vector not working'
def test_l2_matrix():
inpt = T.matrix()
norm = l2(inpt)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
assert f(test_matrix) == 10080.53, 'l2 norm for matrix not working'
def test_l2_vector():
inpt = T.vector()
norm = l2(inpt)
f = theano.function([inpt], norm, mode='FAST_COMPILE')
assert f(test_arr) == 6, 'l2 norm for vector not working'
